The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan
This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety s...
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doaj-0f37b819f1924a6f85d2615de946923c2020-11-25T01:27:35ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/967140967140The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in TaiwanHung-Chang Liao0Meng-Hao Chen1Ya-huei Wang2Department of Health Services Administration, Chung Shan Medical University, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, TaiwanDepartment of Health Services Administration, Chung Shan Medical University, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, TaiwanDepartment of Applied Foreign Languages, Chung Shan Medical University, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, TaiwanThis study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers.http://dx.doi.org/10.1155/2014/967140 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hung-Chang Liao Meng-Hao Chen Ya-huei Wang |
spellingShingle |
Hung-Chang Liao Meng-Hao Chen Ya-huei Wang The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan The Scientific World Journal |
author_facet |
Hung-Chang Liao Meng-Hao Chen Ya-huei Wang |
author_sort |
Hung-Chang Liao |
title |
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan |
title_short |
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan |
title_full |
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan |
title_fullStr |
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan |
title_full_unstemmed |
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan |
title_sort |
study of the optimal parameter settings in a hospital supply chain system in taiwan |
publisher |
Hindawi Limited |
series |
The Scientific World Journal |
issn |
2356-6140 1537-744X |
publishDate |
2014-01-01 |
description |
This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers. |
url |
http://dx.doi.org/10.1155/2014/967140 |
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